Coincident lidar and field measurements in 2016 (Fig. 2) were used to develop a lidar-biomass model for carbon losses from canopy turnover.

Carbon losses from tree and branch fall during the El Niño (1.22 Mg C ha-1 yr-1) were similar to the Amazon forest carbon sink in average years, consistent with the observed increase in carbon emissions from the Amazon region from OCO-2, aircraft profiles, and tower measurements.

Our findings highlight the need to account for drought-induced mortality and branch losses in ecosystem models to capture the long-term impact of drought on Amazon forest carbon cycling.

Data Sources:

Technical Description of Figures

Graphic 1: A time series of high-density lidar data (2013, 2014, and 2016) was used to identify canopy turnover events (green outlines) between 2014 (a) and 2016 (b). (c) Turnover events mapped in the field are shaded purple, and blue dots indicate stem locations for tree fall and multiple tree fall turnover events, including both canopy and understory trees.

Amazon forests store and cycle large amounts of carbon. Projected increases in drought frequency and intensity threaten both forest carbon stocks and biodiversity. The response of Amazon forests to contemporary drought conditions is therefore a critical indicator of a potential climate-driven Amazon forest dieback. In contrast to previous experimental studies, the large-area survey possible with airborne lidar data indicated that the 2015-2016 El Niño drought impacted trees of all sizes, not only tall canopy trees thought to be more vulnerable to hydraulic failure. In addition, this is the first study to quantify carbon losses from branch and tree fall using field data on woody debris and collateral damages to understory vegetation. Our study found that > 80% of woody debris production was from tree falls, despite a higher frequency of branch fall events. These results provide new constraints on the dynamism of Amazon forests under average and drought conditions needed to improve ecosystem models and surface reflectance products.

The extent and degree of spatial change in boreal ecotone tree cover: a baseline estimate from 30 m

Forest patterns at 30 m in sparse and open canopy forests across North America and Eurasia, reveal important differences in the structure of the biome boundary that can be used to monitor future change from climate warming.

Data Sources:

Technical Description of Figures

Two examples from our circumpolar tiaga-tundra ecotone (TTE) map. The extent of the circumpolar TTE is based on Landsat-derived tree canopy cover (TCC) estimates. These estimates include calibrated TCC, modelled TCC uncertainty, and rate of TCC spatial change (TCC abruptness; shown below - top row). Such TCC characteristics help define the extent of the TTE domain, divide it into general zones (shown below- bottom row), and quantify how forest structure varies across the TTE. This estimates will be part of a classification that incorporates topography to quantify forest patterns in sparse and open canopy forests across North America and Eurasia, revealing important differences in the structure of the biome boundary that can be used to monitor future change.

Providing an accurate assessment of the current extent of the northern forest limit is of paramount importance to understand impacts from global climate warming. A detailed asssessment of this biome boundary with uncertainites is required because a majority of tree canopy cover is diffuse and difficult to monitor with moderate resolution data.